Comparison between the genders for the ages and types¶

Questions

What are the differences between the gender for the different combinations of ages and types?
Do we observe the same changes as globally?

Loads¶

Libraries and functions¶

Warning message in is.na(x[[i]]):
“is.na() applied to non-(list or vector) of type 'environment'”Warning message in rsqlite_fetch(res@ptr, n = n):
“Don't need to call dbFetch() for statements, only for queries”

==========================================================================
*
*  Package WGCNA 1.63 loaded.
*
*    Important note: It appears that your system supports multi-threading,
*    but it is not enabled within WGCNA in R. 
*    To allow multi-threading within WGCNA with all available cores, use 
*
*          allowWGCNAThreads()
*
*    within R. Use disableWGCNAThreads() to disable threading if necessary.
*    Alternatively, set the following environment variable on your system:
*
*          ALLOW_WGCNA_THREADS=<number_of_processors>
*
*    for example 
*
*          ALLOW_WGCNA_THREADS=4
*
*    To set the environment variable in linux bash shell, type 
*
*           export ALLOW_WGCNA_THREADS=4
*
*     before running R. Other operating systems or shells will
*     have a similar command to achieve the same aim.
*
==========================================================================


Allowing multi-threading with up to 4 threads.
[1] "preparing gene to GO mapping data..."
[1] "preparing IC data..."
[1] "preparing gene to GO mapping data..."
[1] "preparing IC data..."
[1] "preparing gene to GO mapping data..."
[1] "preparing IC data..."

Data¶

Stats¶

Differentially expressed genes¶

  M VS F (SPF, 8w)    M VS F (GF, 8w)  M VS F (SPF, 52w)   M VS F (GF, 52w) 
         0.4890333          0.4714286          0.4541775          0.4871488 
M VS F (SPF, 104w)  M VS F (GF, 104w) 
         0.3862069          0.8842105

Warning message in pcls(G):
“initial point very close to some inequality constraints”Warning message in pcls(G):
“initial point very close to some inequality constraints”Warning message in pcls(G):
“initial point very close to some inequality constraints”Warning message in pcls(G):
“initial point very close to some inequality constraints”Warning message in pcls(G):
“initial point very close to some inequality constraints”Warning message in pcls(G):
“initial point very close to some inequality constraints”Warning message in stack.default(getgo(rownames(l$deg), "mm10", "geneSymbol")):
“non-vector elements will be ignored”Warning message in stack.default(getgo(rownames(as.data.frame(l$deg)), "mm10", "geneSymbol", :
“non-vector elements will be ignored”

Comparison of the numbers per ages¶

Differentially expressed genes

DEG into gene co-expression network¶

White: up-regulated
Black: down-regulated

M vs F	8w	52w	104w
SPF
GF

GO analysis¶

Biological process¶

Dot-plot with the most over-represented BP GO (20 most significant p-values for the different comparison)

Using term, id as id variables
Using term, id as id variables

Network based on description similarity

M vs F	8w	52w	104w
SPF
GF

M VS F (SPF, 8w)¶

GO Tree at "../results/dge/gender-effect/gender_type_age/go/M_VS_F_SPF_8w.png"

M VS F (GF, 8w)¶

GO Tree at "../results/dge/gender-effect/gender_type_age/go/M_VS_F_GF_8w.png"

M VS F (SPF, 52w)¶

GO Tree at "../results/dge/gender-effect/gender_type_age/go/M_VS_F_SPF_52w.png"

M VS F (GF, 52w)¶

GO Tree at "../results/dge/gender-effect/gender_type_age/go/M_VS_F_GF_52w.png"

M VS F (SPF, 104w)¶

GO Tree at "../results/dge/gender-effect/gender_type_age/go/M_VS_F_SPF_104w.png"

M VS F (GF, 104w)¶

GO Tree at "../results/dge/gender-effect/gender_type_age/go/M_VS_F_GF_104w.png"

Cellular components¶

Dot-plot with the most over-represented CC GO (20 most significant p-values for the different comparison)

Using term, id as id variables
Using term, id as id variables

Molecular functions¶

Dot-plot with the most over-represented MF GO (20 most significant p-values for the different comparison)

Using term, id as id variables
Using term, id as id variables

KEGG pathways¶

Warning message in file.rename(from = paste("mmu", cat, ".pathview.multi.png", sep = ""), :
“cannot rename file 'mmu03010.pathview.multi.png' to '../results/dge/gender-effect/gender_type_age/kegg/over_repr_kegg/mmu03010.pathview.multi.png', reason 'No such file or directory'”

Error in `$<-.data.frame`(`*tmp*`, "labels", value = c("", "", "", "", : replacement has 34 rows, data has 48
Traceback:

1. plot_kegg_pathways(gender_age_type_deg$over_represented_KEGG[, 
 .     "category"], gender_age_type_deg$fc_deg, "../results/dge/gender-effect/gender_type_age/kegg/over_repr_kegg/")
2. suppressMessages(pathview(gene.data = fc_deg, pathway.id = cat, 
 .     species = "Mus musculus", gene.idtype = "Symbol"))
3. withCallingHandlers(expr, message = function(c) invokeRestart("muffleMessage"))
4. pathview(gene.data = fc_deg, pathway.id = cat, species = "Mus musculus", 
 .     gene.idtype = "Symbol")
5. `$<-`(`*tmp*`, "labels", value = c("", "", "", "", "", "", "", 
 . "", "", "", "", "", "", "", "", "", "", "", "", "", "", "", "", 
 . "", "", "", "", "", "", "", "", "", "", ""))
6. `$<-.data.frame`(`*tmp*`, "labels", value = c("", "", "", "", 
 . "", "", "", "", "", "", "", "", "", "", "", "", "", "", "", "", 
 . "", "", "", "", "", "", "", "", "", "", "", "", "", ""))
7. stop(sprintf(ngettext(N, "replacement has %d row, data has %d", 
 .     "replacement has %d rows, data has %d"), N, nrows), domain = NA)

Pathway graphs available at ../results/dge/type-effect/type_gender_age/over_repr_kegg/

Pathway graphs available at ../results/dge/type-effect/type_gender_age/under_repr_kegg/

	Wald padj < 0.05	LFC > 0 (Wald padj < 0.05)	LFC < 0 (Wald padj < 0.05)
M VS F (SPF, 8w)	2462	1291	1171
M VS F (GF, 8w)	2730	1419	1311
M VS F (SPF, 52w)	3459	1735	1724
M VS F (GF, 52w)	3346	1689	1657
M VS F (SPF, 104w)	290	148	142
M VS F (GF, 104w)	95	40	55